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学者姓名：陈艳艳
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Abstract ：
The examination of highway travel behaviour during the COVID-19 pandemic can provide valuable insights into the impacts of the pandemic and associated policies on human mobility patterns. This paper proposes a comprehensive examination, measurement and characterisation approach in the perspective of network and community structure. To capture the changes in travel behaviour, four stages were defined based on four consecutive Augusts from 2019 to 2022, during which varying levels of restrictions were implemented. The findings reveal interesting trends in travel patterns. In 2020, after the clearance of pandemic cases, there was a remarkable increase of over 10% in highway trips. However, in 2021, with the emergence of COVID-19 variants, there was a significant decline of over 30% in highway trips. By employing complex network analysis, key metrics of the primary network, including link weight, node flux and network connectivity, exhibited a notable decrease during the pandemic. These changes in network properties also reflect the spatial heterogeneity of highway travel demand. Moreover, the outcomes of community detection shed light on the evolution of the highway community structure, highlighting the efficacy of a community-collaboration strategy for highway management during public emergency events, as it fosters strong local interaction within the community.
Keyword ：
community detection community detection highway transaction dataset highway transaction dataset complex network analysis complex network analysis COVID-19 pandemic COVID-19 pandemic travel behaviour travel behaviour
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| GB/T 7714 | Liu, Weizheng , Chen, Yanyan . Exploring the Highway Travel Patterns Affected by COVID-19 through Outbreak to Recovery Stages - A Case Study in Guizhou [J]. | PROMET-TRAFFIC & TRANSPORTATION , 2024 , 36 (3) : 478-491 . |
| MLA | Liu, Weizheng 等. "Exploring the Highway Travel Patterns Affected by COVID-19 through Outbreak to Recovery Stages - A Case Study in Guizhou" . | PROMET-TRAFFIC & TRANSPORTATION 36 . 3 (2024) : 478-491 . |
| APA | Liu, Weizheng , Chen, Yanyan . Exploring the Highway Travel Patterns Affected by COVID-19 through Outbreak to Recovery Stages - A Case Study in Guizhou . | PROMET-TRAFFIC & TRANSPORTATION , 2024 , 36 (3) , 478-491 . |
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Abstract ：
Drivers' fault emergency response behavior can easily lead to crashes, resulting in significant economic and property losses. Exploring the causes of improper emergency response behavior is crucial for regulating driver behavior and preventing crash. Therefore, based on crashes data between commercial motor vehicles (CMVs) and noncommercial motor vehicles (NCMVs) that occurred in China from 2014 to 2018, this study established a binary logistic regression model. It systematically analyzed the key factors influencing drivers' fault emergency response behaviors in terms of individuals, vehicles, road conditions, environment, and corporate management. Additionally, it compared the differences in the influencing factors of fault emergency response behaviors between drivers of CMV and NCMV. The results indicate that the model fits well. The presence of faulty emergency response behavior in drivers is significantly correlated with five factors: age, gender, fatigue driving, speeding, and weather conditions. Moreover, these factors have different impacts on CMV drivers and NCMV drivers. Fatigue driving and speeding have a more significant impact on CMV drivers, while other factors are more pronounced for NCMV drivers. This study can provide valuable insights for the development of measures aimed at reducing the severity of CMV-NCMV crashes.
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| GB/T 7714 | Wei, Panyi , Huang, Jianling , Chen, Yanyan et al. Analysis of Influencing Factors of Drivers' Fault Emergency Response Behavior in CMV-NCMV Crashes [J]. | JOURNAL OF ADVANCED TRANSPORTATION , 2024 , 2024 . |
| MLA | Wei, Panyi et al. "Analysis of Influencing Factors of Drivers' Fault Emergency Response Behavior in CMV-NCMV Crashes" . | JOURNAL OF ADVANCED TRANSPORTATION 2024 (2024) . |
| APA | Wei, Panyi , Huang, Jianling , Chen, Yanyan , Ma, Jianming , Zhang, Yunchao , Wang, Shaohua et al. Analysis of Influencing Factors of Drivers' Fault Emergency Response Behavior in CMV-NCMV Crashes . | JOURNAL OF ADVANCED TRANSPORTATION , 2024 , 2024 . |
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Abstract ：
Autonomous intersection management systems aim to efficiently control connected and autonomous vehicles at urban intersections. However, current driving behavior models face challenges in accurately capturing the distinctive human driver characteristics specific to intersection interactions. This article introduces a human-like driving behavior model based on the driver's risk field (DRF) for intersection scenarios. The DRF represents the driver's belief regarding the likelihood of an event occurring, and the associated cost function is determined by the consequences of said event. A driving simulation experiment was conducted at a signalized intersection to evaluate the model, and the results were compared with a human-like driving behavior model. The results show that the proposed model has a high degree of fit. Furthermore, a statistical analysis of the data distribution demonstrates that the predictions generated by the driver model align closely with the driving behavior observed in the signalized intersection experiment.
Keyword ：
Vehicle dynamics Vehicle dynamics Logic Logic Roads Roads Data models Data models Behavioral sciences Behavioral sciences Vehicles Vehicles Costs Costs
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| GB/T 7714 | Hu, Weichao , Chen, Yanyan , Xu, Wenxiang et al. Modeling Human-Like Driving Behavior at a Signal Intersection Based on Driver Risk Field Model [J]. | IEEE INTELLIGENT TRANSPORTATION SYSTEMS MAGAZINE , 2024 . |
| MLA | Hu, Weichao et al. "Modeling Human-Like Driving Behavior at a Signal Intersection Based on Driver Risk Field Model" . | IEEE INTELLIGENT TRANSPORTATION SYSTEMS MAGAZINE (2024) . |
| APA | Hu, Weichao , Chen, Yanyan , Xu, Wenxiang , Mu, Hongzhang . Modeling Human-Like Driving Behavior at a Signal Intersection Based on Driver Risk Field Model . | IEEE INTELLIGENT TRANSPORTATION SYSTEMS MAGAZINE , 2024 . |
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The rapid expansion of urban rail transit necessitates accurate short-term passenger flow forecasts (STPFF) to optimize operation plans and enhance service quality. However, the existing STPFF methods do not fully consider the effect of built environment on passenger flow. In this regard, a convolutional long short-term memory neural network (CNN-LSTM) model incorporating built environment indicators has been proposed for accurately short-term passenger flow predictions. First, a system of built environment indicators (including 11 indicators), anchored in the 5Ds framework, is introduced to depict the characteristics of the built environments surrounding rail transit stations. Then, the random forest model (RF) is utilized to measure and rank the indicator importance. Finally, using historical passenger flow and key built environment indicators as input variables, a CNN-LSTM model for short-term passenger flow forecast is built. Taking Beijing city, China as an example for empirical research, the results show that CNN-LSTM model considering built environment can improve the accuracy of STPFF. Utilizing the top four key built environment indicators (the ratio of commercial land area, density of point of interest (POI) categories, and bus station density) as input variables can effectively reduce model computational complexity while concurrently enhancing predictive accuracy. The highest forecasting accuracy of the model is achieved at a time granularity of 5 min. This study can effectively support the operation and management of urban rail transit.
Keyword ：
Built environment Built environment Convolutional long short-term memory neural network (CNN-LSTM) Convolutional long short-term memory neural network (CNN-LSTM) Urban rail transit Urban rail transit Short-term passenger flow forecast (STPFF) Short-term passenger flow forecast (STPFF)
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| GB/T 7714 | Cao, Bingxin , Li, Yongxing , Chen, Yanyan et al. A CNN-LSTM Model for Short-Term Passenger Flow Forecast Considering the Built Environment in Urban Rail Transit Stations [J]. | JOURNAL OF TRANSPORTATION ENGINEERING PART A-SYSTEMS , 2024 , 150 (11) . |
| MLA | Cao, Bingxin et al. "A CNN-LSTM Model for Short-Term Passenger Flow Forecast Considering the Built Environment in Urban Rail Transit Stations" . | JOURNAL OF TRANSPORTATION ENGINEERING PART A-SYSTEMS 150 . 11 (2024) . |
| APA | Cao, Bingxin , Li, Yongxing , Chen, Yanyan , Yang, Anan . A CNN-LSTM Model for Short-Term Passenger Flow Forecast Considering the Built Environment in Urban Rail Transit Stations . | JOURNAL OF TRANSPORTATION ENGINEERING PART A-SYSTEMS , 2024 , 150 (11) . |
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Abstract ：
A novel re-entrant honeycomb metamaterial based on 3D-printing technology is proposed by introducing chiral structures into diamond honeycomb metamaterial (DHM), named chiral-diamond-combined honeycomb metamaterial (CDCHM), and has been further optimized using the assembly idea. Compared with the traditional DHM, the CDCHM has better performance in static and vibration isolation. The static and vibration properties of the DHM and CDCHM are investigated by experiments and simulations. The results show that the CDCHM has a higher load-carrying capacity than that of the DHM. In addition, the vibration isolation optimal design schemes of the DHM and CDCHM are examined by experiments and simulations. It is found that the vibration suppression of the CDCHM is also improved greatly. In particular, the optimization approach with metal pins and particle damping achieves a wider bandgap in the low-frequency region, which can strengthen the suppression of low-frequency vibrations. And the introduction of particle damping can not only design the frequency of the bandgap via the alteration of the dosage, but also enhance the damping of the main structure. This work presents a new design idea for metamaterials, which provides a reference for the collaborative design of the static and vibration properties of composite metamaterials.
Keyword ：
vibration isolation vibration isolation re-entrant honeycomb re-entrant honeycomb metamaterial metamaterial static properties static properties bandgap bandgap
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| GB/T 7714 | Yong, Jiawang , Dong, Yiyao , Wan, Zhishuai et al. Collaborative Design of Static and Vibration Properties of a Novel Re-Entrant Honeycomb Metamaterial [J]. | APPLIED SCIENCES-BASEL , 2024 , 14 (4) . |
| MLA | Yong, Jiawang et al. "Collaborative Design of Static and Vibration Properties of a Novel Re-Entrant Honeycomb Metamaterial" . | APPLIED SCIENCES-BASEL 14 . 4 (2024) . |
| APA | Yong, Jiawang , Dong, Yiyao , Wan, Zhishuai , Li, Wanting , Chen, Yanyan . Collaborative Design of Static and Vibration Properties of a Novel Re-Entrant Honeycomb Metamaterial . | APPLIED SCIENCES-BASEL , 2024 , 14 (4) . |
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Abstract ：
The occurrence of accidents in expressway weaving areas is significantly influenced by frequent lane change maneuvers. Acquiring the lane change behavior pattern characteristics of vehicles in this area can provide prior knowledge for autonomous vehicles when performing lane change maneuvers, which helps ensure the safety of autonomous vehicles. This study aims to extract lane change behavior patterns of vehicles in weaving areas, to analyze the distribution differences of patterns across different lane change maneuvers, and to explore risk characteristics during the lane change process. First, a lane-changing sequence segmentation method was designed based on the hierarchical Dirichlet process hidden semi-Markov model (HDP-HSMM) algorithm, taking into account the interaction with surrounding vehicles and risk factors. Second, the Gaussian mixture model latent Dirichlet allocation (GMM-LDA) algorithm was employed to cluster the segments and derive patterns of lane-changing behavior that include risk attributes. The trajectory data from the UCF SST dataset were used to validate the method framework and make an in-depth analysis. The results show that the behavior patterns obtained by this method are able to better describe the operational and risk states of the vehicle. Variations exist in the behavioral patterns of different types of lane change maneuvers throughout the entire process. Spatial distribution disparities exist in the behavior patterns of lane change maneuvers across various sections of weaving areas. The findings of this study provide behavioral characteristics of different types of lane change maneuvers in weaving areas, which might contribute to enhancing the accurate recognition of lane change behaviors by autonomous vehicles.
Keyword ：
Driving patterns Driving patterns Expressway weaving areas Expressway weaving areas Primitive segmentation Primitive segmentation Lane change maneuvers Lane change maneuvers Crash risk Crash risk
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| GB/T 7714 | Guo, Yinjia , Gu, Xin , Chen, Yanyan et al. Lane Change Behavior Patterns and Risk Analysis in Expressway Weaving Areas: Unsupervised Data-Mining Method [J]. | JOURNAL OF TRANSPORTATION ENGINEERING PART A-SYSTEMS , 2024 , 150 (11) . |
| MLA | Guo, Yinjia et al. "Lane Change Behavior Patterns and Risk Analysis in Expressway Weaving Areas: Unsupervised Data-Mining Method" . | JOURNAL OF TRANSPORTATION ENGINEERING PART A-SYSTEMS 150 . 11 (2024) . |
| APA | Guo, Yinjia , Gu, Xin , Chen, Yanyan , Guo, Jifu , Wan, Huaiyu , Zhou, Yuntong . Lane Change Behavior Patterns and Risk Analysis in Expressway Weaving Areas: Unsupervised Data-Mining Method . | JOURNAL OF TRANSPORTATION ENGINEERING PART A-SYSTEMS , 2024 , 150 (11) . |
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How to effectively and accurately evaluate and analyze the volatility and reliability of travel speed on urban road before and after students back to school is a hot and key problem in urban road traffic congestion governance research. The Beijing 3rd Ring Road was taken as the research object and the impacts of the students back to school on the volatility and reliability of the travel speed of road sections were qualitatively and quantitatively analyzed based on the road section travel speed data during the weekday morning peak (7:00-8:59). The results showed that the travel speed of the Beijing 3rd Ring Road had cyclicity, time variability, large-scale volatility, and light congestion during the weekday morning peak, and the volatility and reliability indexes of the travel speed of road sections significantly decreased under the impact of the students back to school. The data showed that after the students back to school, the maximum reduction ratio of average travel speed was larger than 55%, and the maximum travel speed reliability reduction value was larger than 0.85 based on the evaluation model of travel speed reliability of car commuters. The research results provide data and theoretical support for urban road traffic congestion mitigation and governance.
Keyword ：
commuting traffic commuting traffic travel speed reliability travel speed reliability urban road traffic urban road traffic travel speed volatility travel speed volatility traffic congestion traffic congestion
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| GB/T 7714 | Li, Jiaxian , Chen, Yanyan , Yang, Xiaoguang et al. Analysis of the Impacts of Students Back to School on the Volatility and Reliability of Travel Speed on Urban Road [J]. | APPLIED SCIENCES-BASEL , 2024 , 14 (5) . |
| MLA | Li, Jiaxian et al. "Analysis of the Impacts of Students Back to School on the Volatility and Reliability of Travel Speed on Urban Road" . | APPLIED SCIENCES-BASEL 14 . 5 (2024) . |
| APA | Li, Jiaxian , Chen, Yanyan , Yang, Xiaoguang , Yuan, Ye . Analysis of the Impacts of Students Back to School on the Volatility and Reliability of Travel Speed on Urban Road . | APPLIED SCIENCES-BASEL , 2024 , 14 (5) . |
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Abstract ：
With the objectives of achieving "peak carbon" and "carbon neutrality", accurately quantifying the carbon emissions of road transportation becomes crucial. It is challenging to accurately describe the energy consumption of vehicles at both temporal and spatial scales from a macro perspective. Therefore, focusing on the quantitative model of vehicle micro energy consumption and road meso energy consumption, this paper reviewed and summarized the energy consumption model of road traffic in terms of data collection, quantification accuracy, and scope of application. Based on this analysis, this paper identifies the challenges of the current road traffic energy consumption model. Finally, we look forward to future research directions for studying quantitative models of energy consumption from road transportation.
Keyword ：
energy consumption quantification models energy consumption quantification models road transportation road transportation carbon emissions carbon emissions
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| GB/T 7714 | Chen, Yanyan , Li, Siyang , Li, Yanan et al. A Review on Quantitative Energy Consumption Models from Road Transportation [J]. | ENERGIES , 2024 , 17 (1) . |
| MLA | Chen, Yanyan et al. "A Review on Quantitative Energy Consumption Models from Road Transportation" . | ENERGIES 17 . 1 (2024) . |
| APA | Chen, Yanyan , Li, Siyang , Li, Yanan , Amara, Yacine . A Review on Quantitative Energy Consumption Models from Road Transportation . | ENERGIES , 2024 , 17 (1) . |
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Abstract ：
Objectives: The potential virus in transportation facilities poses a serious risk to travelers. This research focus on the commuting by metro on the risk of the coronavirus disease 2019 (COVID-19). The main purpose is to explore the trajectory of virus transmission and the effectiveness of various control measures.Methods: A transmission model was established on the basis of the susceptible-infected-recovered (SIR) model, combined with the spatial and temporal characteristics of the metro passenger flow. The implementation effects of the emergency strategies were analyzed through a series of simulation experiments. The changes in passenger flow affected by the virus transmission were analyzed both under the single intervention condition of the disinfection or off-peak travel policy and their double interventions.Results: The results of the experiments show that disinfection and off-peak travel can effectively reduce the number of the infected people. To promote the disinfection is better than the off-peak travel strategy. The optimal solution is the combination of these two strategies, thereby reducing the infection rate in the stations effectively. In particular, it can reduce the number of potential infected people in high-traffic stations by 50%.Conclusions: This study provides a scientific basis for the prevention of COVID-19 in the urban transportation system and the formulation of public emergency strategies. It can also be applied to other epidemic diseases such as the seasonal flu, for public health prevention.
Keyword ：
COVID-19 COVID-19 Travel health Travel health Metro passenger flow Metro passenger flow Virus transmission Virus transmission Emergency response Emergency response
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| GB/T 7714 | Zhou, Yuyang , Zheng, Shuyan , Feng, Feng et al. Passenger flow analysis and emergency response simulation in a metro network using virus transmission model [J]. | JOURNAL OF TRANSPORT & HEALTH , 2023 , 28 . |
| MLA | Zhou, Yuyang et al. "Passenger flow analysis and emergency response simulation in a metro network using virus transmission model" . | JOURNAL OF TRANSPORT & HEALTH 28 (2023) . |
| APA | Zhou, Yuyang , Zheng, Shuyan , Feng, Feng , Chen, Yanyan . Passenger flow analysis and emergency response simulation in a metro network using virus transmission model . | JOURNAL OF TRANSPORT & HEALTH , 2023 , 28 . |
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Abstract ：
Parking problems in garages are rising with the expansion of garage scale, which makes the parking process more challenging for drivers. Driving the wrong way in parking lots is a regular occurrence, and it may cause harmful phenomena such as vehicle scratches, road congestion, and extra carbon emissions. Drivers' wrong-way driving (WWD) behavior in parking lots needs to be studied to improve parking efficiency and safety. In this regard, a subjective questionnaire was designed, including the WWD scale, attitude scale, risk perception scale, legal knowledge scale, existing type-A behavior pattern (TABP) scale, and driver skills scale, and 292 valid samples were obtained for analysis. The reliability and validity of the scales were verified, and a structural equation model (SEM) was established to analyze the effects of TABP, attitude, risk perception, driver skills, and legal knowledge on WWD. The results indicated that the correlative relation between TABP and safety motivation is weak, but TABP affects drivers' attitudes and risk perception (they may affect WWD), and attitudes towards WWD and breaking the rules both affect drivers' WWD behavior. Drivers' driving skill and legal knowledge have no relationship with WWD in parking lots. These findings provide a theoretical basis for optimizing facilities and formulating policies for garages.
Keyword ：
Wrong-way driving (WWD) behavior Wrong-way driving (WWD) behavior Parking lots Parking lots Structural equation model (SEM) Structural equation model (SEM) Influence factors analysis Influence factors analysis
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| GB/T 7714 | Chen, Hepeng , Li, Yongxing , Chen, Yanyan et al. Influence Factors Analysis for Wrong-Way Driving Behavior in Parking Lots [J]. | JOURNAL OF TRANSPORTATION ENGINEERING PART A-SYSTEMS , 2023 , 149 (9) . |
| MLA | Chen, Hepeng et al. "Influence Factors Analysis for Wrong-Way Driving Behavior in Parking Lots" . | JOURNAL OF TRANSPORTATION ENGINEERING PART A-SYSTEMS 149 . 9 (2023) . |
| APA | Chen, Hepeng , Li, Yongxing , Chen, Yanyan , Li, Chen , Guo, Jifu , Olivier, Ngoko Chinkam . Influence Factors Analysis for Wrong-Way Driving Behavior in Parking Lots . | JOURNAL OF TRANSPORTATION ENGINEERING PART A-SYSTEMS , 2023 , 149 (9) . |
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